A novel algorithm for maximum power point tracking (MPPT) in solar power generation systems was proposed and compared with the conventional methods of hill climbing (HC) and perturbation and observation (P&O) algorithms. The two conventional algorithms are prone to divergence under low irradiance levels (<150 W/m 2 ), resulting in difficulties in MPPT. The MPPT technique proposed in this study integrates irradiance change per unit area threshold control (ICPUATC) into the P&O algorithm. The proposed algorithm can facilitate quick and precise convergence at the maximum power point (MPP) for a photovoltaic module under a low irradiance level of 65 W/m 2 . The proposed and HC algorithms were compared for irradiance levels of 480, 140, and 65 W/m 2 , and the proposed algorithm consistently yielded better results than did the HC algorithm.This version has been created for advance publication by formatting the accepted manuscript. Some editorial changes may be made to this version.

The traditional perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm of a structure is simple and low-cost. However, the P&O algorithm is prone to divergence under solar radiation when the latter varies rapidly and the P&O algorithm cannot track the maximum power point (MPP) under partial shading conditions (PSCs). This study proposes an algorithm from the P&O algorithm combined with the solar radiation value detection scheme, where the solar radiation value detection is based on the solar photovoltaic (SPV) module equivalent conductance threshold control (CTC). While the proposed algorithm can immediately judge solar radiation, it also has suitable control strategies to achieve the high efficiency of MPPT especially for the rapid change in solar radiation and PSCs. In the actual test of the proposed algorithm and the P&O algorithm, the MPPT efficiency of the proposed algorithm could reach 99% under solar radiation, which varies rapidly, and under PSCs. However, in the P&O algorithm, the MPPT efficiency was 96% under solar radiation, which varies rapidly, while the MPPT efficiency was only 80% under PSCs. Furthermore, in verifying the experimental results, the proposed algorithm’s performance was higher than the P&O algorithm.